Optimal deployment of mobile cloudlets for mobile applications in edge computing

In the evolution of Internet of Things and 5G networks, edge computing, as an emerging computing paradigm, can effectively reduce the latency of accessing the cloud service and enhance the computing power for resource-constrained user devices. However, in existing communication scenarios, there are still situations where the infrastructure coverage is limited or devices are not covered. At the same time, device location changes constantly due to users’ uncertain mobility. In response to such situations, mobile and flexible equipment combined with cloudlet is used to achieve mobile deployment of cloudlets and provides computing power support for user devices. In this paper, a dynamic cloudlet deployment method based on clustering algorithm (DCDM-CA) is proposed to solve the problem of deploying mobile cloudlets for mobile applications. DCDM-CA determines the cloudlet deployment destination based on the geographic location of multiple devices and the number of tasks generated by multiple devices in a unit time period. In addition, the task offloading is optimized after deploying cloudlets to minimize the system response latency. Extensive simulations reveal that DCDM-CA can efficiently deploy mobile cloudlets, and the system response latency is minimized through optimizing task offloading.